PSPNet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1378 stars · 243 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Reference implementation of the Pyramid Scene Parsing Network (PSPNet), a CVPR 2017 semantic segmentation model that won the ImageNet Scene Parsing Challenge 2016. The original repo provides Caffe/Matlab training and evaluation code, with a modernized PyTorch codebase (semseg) also available from the same author.

Use cases

• train a semantic segmentation model on ADE20K, PASCAL VOC, or Cityscapes
• run scene parsing inference on images with pretrained PSPNet models
• reproduce CVPR 2017 PSPNet research results
• evaluate segmentation models with mIoU metrics
• use PSPNet or PSANet in a PyTorch training pipeline
• benchmark pyramid pooling architectures for dense prediction

When to choose

• you need the official reference implementation of PSPNet for research reproduction
• you want pretrained models for ADE20K, VOC2012, or Cityscapes segmentation
• you are studying pyramid pooling module architectures

When to avoid

• you need a production-ready, actively maintained segmentation library
• you cannot build legacy Caffe with CUDA 7-era dependencies
• you want a simple pip-installable tool rather than research code

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning image-processing cpp python semantic-segmentation pspnet caffe pytorch scene-parsing cvpr2017 research-code linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="hszhao/semseg")